Objective Numerous studies have demonstrated that the spheroidal aerosol model not only offers significant advantages in simulating optical properties but also exhibits high computational efficiency, leading to its widespread adoption in remote sensing retrieval algorithms. Aspect ratio (RAR) is a crucial physical parameter for characterizing the shapes of spheroid aerosols. However, research on the influence of aspect ratio distribution characteristics on the average optical properties of mineral aerosols remains relatively limited. Methods Since aspect ratio distribution characteristics determine the morphologies of spheroidal particles, which are critical to aerosol optical properties, this study explores the relationship between aspect ratio distribution characteristics and mineral aerosol optical properties. Based on the refractive index data from the optical properties of aerosols and clouds (OPAC) database (Fig. 1) and employing a newly developed Lorenz-Mie code that utilizes the separated variable method in spheroidal coordinates, we numerically analyzed the influence of aspect ratio distribution characteristics on the average optical properties of mineral aerosols-including extinction coefficient, single scattering albedo, scattering phase matrix, asymmetry factor, backscattering coefficient, lidar ratio, and linear depolarization ratio-across visible and near-infrared bands. Results and Discussions First, the optical properties of single spheroidal aerosols as a function of RAR were analyzed (Fig. 3). The results indicate that RAR significantly affects the optical properties of single mineral aerosols. Five distinct aspect ratio distribution models (AR1 to AR5) were selected (Fig. 4): AR1 consists of prolate spheroids with RAR = 1.7; AR2 is a mixture of various prolate and oblate spheroids with multiple RAR values; AR3 comprises multiple prolate spheroids with different RAR values, unlike AR1; AR4 uses oblate spheroids with RAR = 0.2; and AR5 represents spheres (RAR = 1). These models exhibit significant differences in morphology and composition. Further analysis revealed that AR4 (oblate spheroids) substantially impacts the average extinction coefficient, single scattering albedo, and asymmetry factor, resulting in large errors. In contrast, AR5 (spheres) shows minor differences compared to AR1, AR2, and AR3, suggesting that spherical approximations can yield similar results in specific scenarios. Scattering and polarization properties (Fig. 6) are highly sensitive to aspect ratio distribution, particularly in the backscattering direction (theta = 180 degrees), underscoring the importance of aspect ratio in backscattering-based applications such as lidar. For backscattering-related properties (Fig. 7), AR1, AR2, and AR3 exhibit similar trends with small differences, while AR4 and AR5 cause significant errors. The lidar ratio, defined as the ratio of extinction coefficient to backscattering coefficient, is inversely proportional to the backscattering coefficient, and the numerical results align with physical principles, verifying calculation correctness. Errors primarily arise from notable differences in P11 and P22/P11 at backscattering directions (Fig. 6). Conclusions In summary, the results demonstrate that aspect ratio significantly influences mineral aerosol optical properties, with substantial errors occurring when only the oblate spheroid model is used (0< RAR < 1). The sensitivity of scattering, linear polarization, and circular polarization properties to aspect ratio distribution varies markedly across scattering angles, especially in the backscattering direction. When only oblate spheroids and spheres are employed to characterize mineral aerosols, these models significantly affect the average backscattering coefficient, lidar ratio, and linear depolarization ratio. Thus, aspect ratio's impact on backscattering-based applications (e.g., lidar engineering) cannot be overlooked, and appropriate spheroid models are essential for accurate lidar-related optical properties. This study enriches the research on mineral aerosol optical properties and provides valuable insights for applications in atmospheric physics, remote sensing, and lidar.

Laser transmission over airborne-to-low-altitude platforms is jointly affected by atmospheric extinction, cloud microphysics, propagation geometry, and atmospheric turbulence. This paper develops a comprehensive laser transmission model for an aircraft-to-unmanned aerial vehicle communication link beneath a spherical cirrus cloud layer, simultaneously accounting for molecular, aerosol, and cloud attenuation, while incorporating atmospheric turbulence through a path-integrated Rytov formulation combined with aperture-averaging effects. Numerical simulations for a 1550 nm laser investigate the impacts of aircraft altitude, geocentric angle, and cirrus ice crystal effective radius on the received power. The results show that the relative contributions of turbulence, cloud extinction, and geometric loss strongly depend on aircraft altitude. At higher altitudes, aperture averaging effectively suppresses turbulence-induced fading, and the received power is primarily governed by cloud and aerosol attenuation. As the aircraft descends, increased path-integrated turbulence and reduced spatial averaging produce clearly observable turbulence-induced power penalties, particularly for low-altitude unmanned aerial vehicle targets. For large geocentric angles combined with low aircraft altitudes, geometric spreading dominates and prevents power recovery even after the propagation path exits the cloud layer. In addition, larger cirrus ice crystal effective radii yield higher received power due to reduced effective extinction associated with strongly forward-peaked scattering at 1550 nm. These results provide quantitative guidance for link budget estimation and system design under complex atmospheric conditions.

Realization of full-link communication in the atmosphere and the water is a crucial area of research, it provides the pace of development of new communications technologies and the impact on the future integration of air, space, and sea. In this paper, we examine the distribution characteristics of the orbital angular momentum of Laguerre–Gaussian (LG) vortex beams in atmospheric and oceanic turbulence, derive analytical expressions for the spiral spectrum of LG vortex beams, and analyze the effects of the wavelengths, transmission paths, and beam intensity on the spectrum within turbulent environments. The findings show that long-wavelength LG vortex beams perform better in turbulent conditions. Blue-green LG vortex beams exhibit significantly enhanced performance in downlink atmospheric transmission compared to uplink transmission. Additionally, greater intensities of atmospheric and oceanic turbulence lead to a more pronounced extension of the spiral spectrum. Oceanic turbulence exerts a greater influence on blue-green LG vortex beams compared to atmospheric turbulence. This paper presents the theoretical foundation for accomplishing two-way blue-green LG vortex beam transmission between the ocean and the atmosphere.

This paper presents a novel tri-band wearable antenna featuring significantly enhanced front-to-back ratio (FBR) through an innovative phase-compensation technique. Operating in the $2.5 \text{GHz}, 3.5 \text{GHz}$, and 5.5 GHz industrial, scientific, and medical (ISM) bands. in this design, a phasetuning structure is established in the middle of the crosseddipole architecture to achieve consistent back radiation suppression across all operational frequencies. The antenna employs strategically positioned L-shaped slot configurations on dipole arms to establish three independent resonant paths, while the central phase-adjusting module maintains optimal 180° phase opposition between radiating elements. The innovative crossed-dipole configuration with optimized phase cancellation yields remarkable FBR values of $12.4 \text{dB}, 8.5 \text{dB}$, and 13.2 dB at $2.45 \text{GHz}, 3.5 \text{GHz}$, and 5.5 GHz, respectively. Comprehensive on-body evaluation confirms stable performance with specific absorption rate (SAR) values compliant with international safety standards, validating the antenna's suitability for wearable applications.

To explore the propagation characteristics of vortex optical fields with special correlation structures in complex turbulent environments, the far-field evolution behaviors of stochastic electromagnetic partially coherent rectangular multi-Gaussian correlated Schell-model vortex (EPC-RMGCSMV) beams in anisotropic turbulence were theoretically investigated in this research. Based on the extended Huygens-Fresnel principle and the anisotropic non-Kolmogorov power spectrum model of atmospheric turbulence, the expression for the cross-spectral density matrix elements of the EPC-RMGCSMV beam in the observation plane is derived.The evolution behaviors of the far-field spectral intensity and the spectral degree of the polarization structure of the EPC-RMGCSMV beams were systematically investigated, and the effects of the beam parameters and turbulence factors on the beam propagation were analyzed in detail. The results indicated that, in the near-field region, the vortex phase dominated, which resulted in a doughnut-shaped spectral density distribution. The central dark core gradually disappeared as propagation distance increased. With the effects of turbulence, the rectangular flat-topped profile in the far-field evolved into a Gaussian-like distribution, and the beam spot size decreased with the stronger anisotropic turbulence. The underlying mechanism was that anisotropic turbulence led to different evolution rates of the spectral density distributions for the x-polarized and y-polarized components, which in turn caused the beam spot became elliptical rather than circular. Moreover, as the anisotropy factor mu x increased, the overall distribution range of the far-field spectral degree of polarization (DOP) narrowed, while the on-axis DOP value remained consistently higher than that in isotropic turbulence. Compared with conventional Gaussian-correlated or scalar vortex beams, the EPC-RMGCSMV beam exhibited stronger resistance to anisotropic turbulence became of its multi-Gaussian correlation structure. These theoretical findings established a foundation for understanding specially correlated vortex beams in complex atmospheric environments, highlighting their potential for free-space optical communications and remote sensing.

An experimental investigation of the transmission of orbital angular momentum carried by Bessel-Gaussian (BG) vortex beams in multi-factor coupled underwater environments is presented. A laboratory-scale marine environment simulation platform is established to enable controlled coupling of temperature gradients, salinity variations, and turbidity levels. The transmission performance of Gaussian and BG vortex beams is comparatively evaluated at a modulation rate of 150 MHz in terms of beam drift variance, scintillation index, optical power attenuation, and bit error rate (BER). The results indicate that coupled environmental disturbances significantly degrade beam stability and communication performance. Compared with Gaussian beams, BG vortex beams exhibit improved robustness under identical conditions, characterized by reduced beam drift, lower scintillation, and enhanced BER performance. These advantages are mainly attributed to the annular energy distribution and phase structure of BG vortex beams, which help mitigate the cumulative effects of environmental perturbations. Based on experimental observations, a semi-empirical attenuation formulation is obtained through experimental fitting, achieving a coefficient of determination of approximately 0.9 within the investigated parameter ranges. The formulation provides an engineering-level method for estimating optical power loss and supporting transmission power selection in complex underwater channels. The results offer practical guidance for the design and performance evaluation of robust underwater optical communication systems. (c) 2026 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI)training, and similar technologies, are reserved.

Optical wave propagation in the ocean constitutes a challenging random-medium problem due to the combined effects of depth-dependent absorption, scattering, and refractive-index fluctuations induced by oceanic turbulence. In this work, we develop a depth-dependent statistical propagation model for vortex beams along slant paths by coupling realistic chlorophyll-induced attenuation profiles with an inclined-path oceanic turbulence spectrum. Based on this framework, the evolution of spatial coherence radius, beam attenuation, and orbital-angular-momentum (OAM) modal crosstalk of Bessel-Gaussian vortex beams is systematically investigated as functions of ocean depth, propagation distance, and turbulence parameters. The results reveal a pronounced depth dependence of beam attenuation governed by the vertical distribution of chlorophyll, as well as significant turbulence-induced degradation of spatial coherence leading to enhanced intermodal coupling among OAM states. As an illustrative application, the proposed model provides a quantitative prediction of the optical power required to sustain long-range underwater propagation, and demonstrates that appropriate optimization of beam parameters can effectively mitigate OAM crosstalk in inhomogeneous oceanic turbulence. These results provide a unified statistical framework for analyzing the propagation and modal evolution of structured optical fields in depth-varying oceanic random media.

Objective With the advantages of high bandwidth, low delay and strong anti-interference ability, underwater wireless optical communication (UWOC) technology has shown important application value in the fields of marine resource exploration, underwater robot control and military confidential communication. However, in the actual ocean transmission, ocean turbulence will lead to the broadening of orbital angular momentum (OAM) spectrum, and the scattering effect of suspended particles will destroy the orthogonality of modes, cause mode crosstalk and bit errors, and seriously restrict the system performance. The existing research has the following problems: environmental modeling is mostly limited to a single turbulence factor, and the coupling analysis of multiple physical fields such as temperature, salinity and turbidity is lacking; the feature focusing ability of the attention mechanism in distinguishing adjacent patterns needs to be improved; there is a trade-off between the performance and efficiency of deep networks in OAM pattern recognition: although complex networks can achieve high recognition accuracy, the computational cost is high; although the training of simple networks is efficient, the misjudgment rate increases significantly under strong turbulence conditions, which restricts the reliability of the system. Methods To solve the above problems, this paper comprehensively considers the effects of temperature gradient, salinity gradient, turbidity, different transmission distances and turbulence intensities on vortex beam pattern recognition, and verifies the robustness of the model in a complex underwater environment; an improved MobileNetV3-Small model based on transfer learning is proposed. The efficient channel attention (ECA) mechanism is introduced to replace the squeeze and excitation (SE) attention mechanism to enhance the feature discrimination ability through local cross-channel interaction, to effectively suppress the misclassification of adjacent OAM patterns, and then enhance the recognition ability of complex OAM patterns, reducing the computational time and improving the recognition accuracy. In addition, through the combination of simulation and experiment, the comprehensive effects of temperature gradient, salinity gradient, turbidity and other environmental factors on vortex pattern recognition are systematically quantified. Results and Discussion The numerical simulation results of the identification performance of underwater OAM at different transmission distances are shown. Under weak turbulence conditions, the model has the highest recognition accuracy at 50 m; as the transmission distance increases to 200 m, the accuracy gradually drops to 97.16 %. Under strong turbulence conditions, the recognition accuracy at 50 m is 97.43 %, and it drops to 92.07 % at 200 m. It can be seen that under both turbulent conditions, the recognition performance of the model shows a downward trend with the increase of distance. This phenomenon can be attributed to the fact that as the transmission distance increases, the intensity attenuation of the vortex beam increases, and the phase distortion caused by turbulence also superimposes, resulting in a decrease in signal quality. Nevertheless, the recognition accuracy of the model within a range of 200 m has always been maintained above 92 %, especially under weak turbulence conditions, fully reflecting its strong robustness in complex marine environments. In the OAM simulation dataset identification task, the performance differences between the accuracy and training time of the four models are compared. The accuracy rate of I-MobileNetV3-Small based on transfer learning reaches 96.0 %, and the training time is 4081 s. Compared with ResNet34, the training time is reduced by 59.2 % and the accuracy loss is 1.3 percentage points. By comparing the ablation experimental data of MobileNetV3-Small, it can be found that under the same network model architecture, the accuracy rate of MobileNetV3-Small using transfer learning increases by 0.5 percentage point and the training time is reduced by 1.1 %, indicating that the transfer learning strategy has an effect on improving model performance. Under the same transfer learning framework, the introduction of ECA mechanism has improved the accuracy of the model by 1.2 percentage points and reduced the training time by 2.6 %. This shows that attention mechanisms can effectively enhance the model's ability to capture turbulent distortion features without increasing computational burden. The model shows strong adaptability and robustness under complex environmental conditions, and the overall recognition accuracy remains above 92 %. Specific analysis shows that in the test1 test environment, the model achieves the highest recognition accuracy. However, when the environmental conditions change, the recognition performance of the model shows a certain fluctuation: when the turbidity is fixed, the recognition accuracy shows a significant downward trend as the temperature and salinity difference increases, which indicates that the changes in temperature and salinity will significantly affect the integrity of the OAM; while when the temperature and salinity difference are fixed, although the recognition accuracy also decreases with the increase of turbidity, the decline is relatively small, indicating that the turbidity has a weak destructive effect on the integrity of the pattern. These results illustrate the degree of influence of environmental factors on OAM recognition, and further illustrate that the I-MobileNetV3-Small model has good robustness in complex environments. Conclusions This study proposes an I-MobileNetV3-Small model based on transfer learning for OAM recognition in complex underwater environments. The simulation results show that the model still maintains a recognition accuracy of 92.07 % under the 200-m transmission condition of strong turbulence, and can reach 97.16 % under the weak turbulence condition. Compared with the ResNet34 model, the training time is reduced by about 59.2 %, and the accuracy gap is controlled within 1.3 percentage points. Through ablation experiment verification, the ECA attention mechanism improves the accuracy of the model by 1.2 percentage points, and the transfer learning strategy brings an improvement in accuracy by 0.5 percentage point. Among the ten underwater environment tests, 100% identification is achieved in a clean water environment. With the changes in temperature and salinity differences, the overall accuracy shows a downward trend. Compared with turbidity, the temperature and salinity differences have a greater impact on OAM identification. Even under strong turbulence, the model can maintain an accuracy of more than 92 %, which fully proves that this network architecture has strong environmental adaptability. Theoretical simulation and experimental results verify the reliability of the model. This method can provide high-precision OAM recognition support for underwater vortex optical communication systems within a range of 200 m.

Wafer warpage and unevenness can lead to chip defects. And vacuum leaks due to warpage during handling can cause insufficient adhesion, leading to issues such as wafer drop, which affects the yield rate. In order to realize the high-precision measurement of warpage and bow of double-sided polished wafers, an interferometric method is proposed in this paper. The method adopts wavelength-tuned interferometry to measure the double-sided polished wafers to record the interferograms, and then utilizes the least-squares algorithm to separate the multi-surface interferometric fringes, which can obtain the front surface, back surface and thickness surface morphology of the double-sided polished wafers. According to the dependence between surface shape and warpage and bow, high precision measurement of warpage and bow of double-sided polished wafers can be realized. The experimental results show that the warpage and bow measured by this method are 0.919 +/- 0.053 mu m and 0.035 +/- 0.005 mu m, respectively. And the method is compared with the wafer warpage stress gauge, which has a warpage and bow of 0.797 mu m and 0.023 mu m, respectively, verifying the effectiveness of the method. The proposed interferometric method improves the measurement accuracy and has good application value.

Objective Unmanned aerial vehicle (UAV) laser communication has become a crucial enabling technology for future space-airground integrated information networks due to its high capacity, enhanced security, and strong anti-interference capabilities. In complex space-air-ground environments, laser communication not only enables high-speed data transmission but also meets stringent requirements for information security, real-time performance, and communication reliability. However, laser transmission through atmospheric channels is susceptible to turbulence interference, while dynamic jitter from UAV platforms introduces pointing errors. The combined effect of these factors significantly degrades the reliability of communication links. Therefore, in-depth research on the optical transmission characteristics under the joint influence of atmospheric turbulence and UAV pointing errors, along with studies on turbulence suppression and adaptive compensation techniques, is essential for enhancing the performance of UAV laser communication systems. This paper addresses the UAV air-to-ground slant-path laser communication link by employing an adaptive subcarrier multiple phase shift keying (MPSK) modulation method to improve system bit error rate (BER) performance under the combined effects of atmospheric turbulence and UAV pointing errors. Through systematic analysis of the impact of modulation strategies, link parameters, and platform dynamics on communication performance, this study provides a theoretical foundation and technical underpinnings for achieving highly reliable air-to-ground slant-path laser communication systems. It also offers valuable reference basis for the design optimization and engineering applications of UAV laser communication systems. Methods Based on the Gamma-Gamma turbulence channel model, this paper constructs a joint statistical model of atmospheric turbulence and UAV pointing errors. The pointing errors are characterized by non-zero boresight deviation and Gaussian-distributed jitter to reflect the impact of dynamic platform jitter on beam transmission. Building upon this model, the asymptotic BER expression for adaptive subcarrier MPSK modulation is derived through integral operations and numerical analysis, providing a theoretical basis for evaluating system performance in complex atmospheric environments. Subsequently, numerical simulations are employed to systematically analyze the influence of key parameters-such as modulation order, zenith angle, beam divergence angle, receiver aperture diameter, and UAV flight altitude-on the system BER. This analysis offers reference data and methodological support for performance optimization and engineering design in UAV air-to-ground slant-path laser communication systems. Results and Discussions Through simulation analysis of the UAV air-to-ground slant-path laser communication link, it can be observed that adaptive subcarrier MPSK modulation effectively improves the system BER. When the modulation order is 8 and the signal-to-noise ratio (SNR) is 60 dB, the system BER is reduced by approximately two orders of magnitude compared to non-adaptive subcarrier binary phase shift keying (BPSK) modulation (Fig. 3). The zenith angle significantly impacts system performance and should be controlled within 60 degrees to ensure link stability (Fig. 6). Under certain pointing error conditions, as the beam divergence angle increases, the BER first decreases and then rises. There exists an optimal beam divergence angle that minimizes the system BER, and this optimal angle increases with higher pointing errors (Fig. 7). Increasing the receiver aperture diameter can effectively reduce the system BER, but the improvement diminishes as pointing errors increase. Additionally, the aperture size is constrained by the UAV's structural and payload limitations (Fig. 8). As the UAV altitude increases, the impact of atmospheric turbulence intensifies significantly, leading to a rise in BER. However, under different pointing error conditions, the differences in BER are relatively small (Fig. 9). This study systematically analyzes the effects of key parameters-such as modulation order, zenith angle, beam divergence angle, receiver aperture diameter, and UAV altitude-on the system BER. It provides theoretical support and practical references for optimizing the performance and engineering design of UAV air-to-ground slant-path laser communication links. Conclusions This study focuses on the UAV air-to-ground slant-path laser communication link. Under the combined effects of atmospheric turbulence and UAV pointing errors, it derives the asymptotic expression for the BER of the air-to-ground slant-path laser communication link using adaptive subcarrier MPSK modulation. The study systematically analyzes the impact of pointing errors, modulation order, zenith angle, beam divergence angle, receiver aperture diameter, and UAV altitude on the system BER. The results indicate that adaptive subcarrier MPSK modulation can effectively improve BER performance and enhance link reliability. When the modulation order is 8 and the SNR is 60 dB, the BER is reduced by approximately two orders of magnitude compared to non-adaptive subcarrier BPSK. When the zenith angle is less than 60 degrees, the impact of turbulence is weaker, resulting in better communication quality. Beam divergence angle, receiver aperture diameter, and UAV altitude all significantly affect the system BER, and reasonable parameter design can further enhance link reliability. This research provides theoretical support and optimization insights for the engineering design of UAV laser communication systems, offering valuable references for parameter selection and anti-interference performance improvement. In future studies, techniques such as efficient channel coding, spatial diversity, and intelligent beam control will be further integrated to enhance system robustness in complex environments. Additionally, an experimental platform will be established to validate the theoretical models and simulation conclusions presented in this paper.

Active control of circular dichroism (CD) in the terahertz (THz) band is pivotal for advancing fields such as sensing, imaging, and communications. This paper presents a tunable chiral metasurface based on the naturally occurring hyperbolic material alpha-molybdenum trioxide (alpha-MoO3) and graphene, comprising a silver (Ag) substrate, an alpha-MoO3 layer, and a top graphene layer. A periodic elliptical aperture array with a specific rotation angle is designed within the alpha-MoO3 layer to break symmetry. Following geometric parameter optimization, the metasurface achieves a CD of 0.98 at 5.47 THz, corresponding to a quality factor (Q-factor) of 162. Crucially, dynamic control of the CD response is realized by tuning the Fermi level of the graphene layer. Further analysis of the x-y cross-sectional electric field distribution at the resonance frequency reveals that the CD response originates from the structure's selective absorption of left-circularly polarized (LCP) and right-circularly polarized (RCP) light. Moreover, the metasurface exhibits excellent robustness to variations in the incident angle. This work provides what we believe to be novel insights for developing chiral biosensors and tunable polarization modulators. (c) 2026 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

Acoustic waves, as mechanical waves, can perturb atmospheric pressure during propagation, altering the refractive index and turbulence distribution. This study explores a method to mitigate the impact of atmospheric turbulence on optical wave transmission using a linear array acoustic source. We investigated the transmission characteristics of vortex beam superposition states under acoustic perturbation, examining the effects of different wave frequencies and propagation distances on the acoustic field distribution, scintillation index, and atmospheric refractive index structure constant. The results show that acoustic field distributions vary with frequency, and a stable acoustic field is achievable with proper configuration. The scintillation index and refractive index structure constant are influenced by both the acoustic wave propagation distance and sound pressure level. Furthermore, a higher sound pressure level of the source enhances the impact of the linear array acoustic waves on both the scintillation index and the atmospheric refractive index structure constant. This research presents a novel approach to improving optical wave transmission by mitigating atmospheric turbulence.

Optical camera communication (OCC) for vehicle-to-everything (V2X) scenarios has emerged as a critical technical pathway in intelligent transportation systems (ITS). However, the coupled interference between background noise and communication signals in complex outdoor environments severely compromises the OCC system's robustness, necessitating precise region-of-interest (ROI) detection algorithms for light source localization to ensure reliable information transmission. To solve this problem, this study proposes a keypoint-based ROI (KP-ROI) detection model and establishes a systematic evaluation framework for V2X communication performance. Integrated with OCC system architecture, this framework defines the detection rate (alpha d) and precision rate (alpha p) to analyze ROI's impact mechanisms on communication quality while employing Undersampled Differential Phase Shift On-Off Keying (UDPSOOK) modulation for experimental validation. The experimental results show that in controlled static scenarios, the proposed algorithm can stably transmit vehicle communication data at a communication distance of 15 m with an average bit error rate (BER) of 0.5%, and supports an angular deflection of +/- 30 degrees. In dynamic scenarios, during straight-line constant-speed driving, the BER can remain stable below 5%. This study verifies the strong correlation between ROI detection robustness and communication efficiency, while demonstrating the advantages of the keypoint algorithm in light source localization tasks.

This paper presents a dual-band polarization-reconfigurable transparent antenna. The antenna is fabricated by etching indium-tin oxide (ITO) transparent conductive film, with a thickness of 0.125 mm, onto a 0.1 mm thick polyester (PET) substrate, achieving an overall light transmittance of 87%. The antenna design comprises two circular monopole patches and a surrounding frame. The circular monopole patches are coupled and fed via T-shaped feedlines. Four diode switches, mounted on the ITO surface using conductive silver paste, enable control over the antenna's polarization. By varying the bias voltage, three polarization states can be realized: linear polarization, left-handed circular polarization, and right-handed circular polarization. The antenna's performance was evaluated through simulation conducted on a vehicular glass substrate. The antenna has size of 96.7x68.9 mm(2) with a total thickness of 0.225 mm. It exhibits a linear polarization matching bandwidth of 2.3-6.5 GHz and a circular polarization bandwidth of 5.4-6.4 GHz (15%).

In conventional binary-modulated optical camera communication (OCC) systems, camera exposure causes inter-symbol interference (ISI), which significantly impacts bit error rate (BER) performance and limits practical applications. We apply orthogonal frequency division multiplexing (OFDM) to OCC, leveraging its anti-interference properties. By modeling the system and analyzing the BER, we find that exposure induces ISI and frequency-selective attenuation. However, adding cyclic prefix and frequency domain equalizer can mitigate these effects, reducing the BER to less than 10(-4) at SNR>20 dB. Our analysis provides a theoretical foundation for optimizing OCC with OFDM modulation.

Objective The single-photon LiDAR is widely utilized in fields such as biology,geology,remote sensing,robotics,and navigation due to its long-range capability and high imaging resolution.When combined with the time-correlated single-photon counting technology,the system can achieve picosecond-level time resolution,enabling the reconstruction of high-resolution depth images.The system has a pulsed laser that emits periodic short pulses toward a target scene and a single-photon detector that counts the reflected photons.By scanning each pixel over an extended period,a photon count of the order of 103 can be achieved for each pixel.This process effectively reduces background noise and detector dark counts and minimizes the range uncertainty caused by photon flight time jitter.These beneficial effects make it possible to realize millimeter-to micrometer-level distance accuracy and high-resolution depth image reconstruction.Traditional methods that rely on repeated measurements have long data acquisition times,limiting the applicability of single-photon LiDAR in dynamic target remote sensing,autonomous driving,and non-line-of-sight imaging.When acquisition times are short and echo signals very weak,only a few photons are detected,leading to a low signal-to-noise ratio(SNR).Reconstructing high-precision depth images with minimal echo photon data under these low-SNR conditions is a major challenge for existing single-photon counting LiDAR technology.To address this challenge,a novel depth image reconstruction algorithm is proposed.This algorithm integrates a photon-counting LiDAR detection probability model with a backpropagation neural network.This approach enhances the accuracy of depth image reconstruction under varying SNR conditions and improves the performance of single-photon LiDAR in complex scenarios. Methods The proposed method improves depth image reconstruction from single-photon LiDAR data under low-SNR conditions.The method comprises three main steps.The first step is filtering based on the photon-counting LiDAR detection theory.This involves windowed processing and adjustments for noise cluster probabilities to enhance the signal by reducing noise.In the second step,a backpropagation neural network fills in the missing pixels,ensuring image continuity.Unlike existing deep-learning approaches,this step eliminates the need for additional datasets.In the final step,total variation regularization is performed to refine the depth image and improve accuracy.This step enhances depth estimation precision and effectively manages the challenges of low SNRs.By combining these techniques,the proposed method significantly improves the depth estimation performance for single-photon LiDAR systems. Results and Discussions Simulations using the Middlebury dataset were performed to evaluate single-photon avalanche diode measurements obtained under different scenes and lighting conditions.The performance of the proposed algorithm was compared with that of the Shin and the Rapp algorithms by measuring the average reconstruction error for the depth images across nine typical noise levels and four test scenarios. The results indicate that under typical noisy conditions,particularly in environments with very low SNRs,the proposed algorithm significantly outperforms the Shin and Rapp algorithms.A comparison of the average reconstruction errors of the three algorithms for different scenes showed that compared to the Shin and Rapp algorithms,the proposed algorithm achieved improvements of 38.67 times and 56％,respectively,in the Art scene;62.07 and 1.05 times,respectively,in the Bowling scene;52.67 and 1.78 times,respectively,in the Laundry scene;and 14.15 times and 42％,respectively,in the Reindeer scene. The Shin algorithm significantly reduced the estimation error when the SNR exceeded 0.05.This improvement is attributed to the algorithm's binomial estimation approach,which efficiently extracts signals and suppresses noise as the SNR increases.The Rapp method performs well at high SNRs but shows a notable decline in performance when the ratio drops to 0.01.Since the Rapp method relies on neighboring pixel photon data,it can effectively distinguish signals under high SNR conditions but is prone to boundary errors in low-SNR scenarios.In the proposed method,although the error increases with rising noise levels below 0.05,the increase rate is slower than that of the Shin and Rapp algorithms,indicating greater robustness of the proposed method under extremely low-SNR conditions. From the perspective of computational efficiency,the average running time of the proposed algorithm is slightly lower than that of the Rapp algorithm but higher than that of the Shin algorithm.Although the Shin algorithm has the shortest run time,it suffers from high reconstruction errors.Thus,the proposed algorithm achieves a better balance of performance and efficiency,making it more suitable for environments with low SNRs. Conclusions Traditional methods work well for reconstructing depth images under high SNRs.However,in low-SNR environments,background noise often hides details of the target objects,making it hard to distinguish them from their surroundings.To tackle this problem,a new depth image reconstruction algorithm is proposed.It combines photon-counting LiDAR models with deep-learning techniques.This algorithm is specifically designed for low-SNR conditions,effectively smoothing depth images while preserving edge details.A comparison with other methods showed that the proposed algorithm greatly reduces the reconstruction errors compared to the existing methods,especially under very low-SNR conditions. The proposed method is expected to enhance the application of photon imaging in challenging scenarios,such as non-line-of-sight and ghost imaging.It can also refine modules in the photon-counting LiDAR image reconstruction,offering potential for future upgrades and customization.

Integrating image sensors’ imaging capabilities into the receiver for visible light communication is a prominent characteristic of optical camera communication (OCC). However, the exposure effect during imaging distorts received waveforms and introduces inter-symbol interference (ISI), leading to decreased OCC reliability. This paper aims to provide an in-depth analysis of the impact of image sensor exposure effects on the error performance of OCC systems. Analytical expressions of the pixel signal-to-interference and noise ratio (PSINR) are derived using the pulse response function (PRF) for an on-off keying (OOK) modulated OCC system with varying exposure times. Furthermore, the bit error rate (BER) performance is evaluated analytically using PSINR, and a straightforward BER measurement scheme is proposed for experimental validation. Results from analyses and experiments conducted under different exposure times indicate that longer exposures lead to increased ISI and decreased PSINR, thereby increasing the error probability of data demodulation. Additionally, a combined impact of noise and exposure on OCC system reliability is observed, highlighting noise-limited and interference-limited characteristics under low and high signal-to-noise ratio (SNR) conditions, respectively. By utilizing PSINR as a bridge, this paper precisely analyzes OCC system reliability under exposure effects, laying a theoretical foundation for system design and optimization.

Constrained by the imaging mechanisms of cameras, the data transmission rate in optical camera communication (OCC) is considerably lower than that in traditional visible light communication (VLC). This Letter introduces a new, to the best of our knowledge, binary modulation scheme designed to increase OCC transmission rates, with the transmitter performing high-order modulation across frequency and phase dimensions and the receiver employing a frequency-domain demodulation approach. This proposed scheme exhibits better scalability and lower implementation complexity than existing schemes. Additionally, the influence of exposure time and readout time parameters of rolling shutter cameras on communication performance has been dissected and confirmed through numerical simulations and experimental validation, laying a theoretical foundation for the design and optimization of the OCC system.